Simultaneous DOA estimation based on Kolmogorov's theorem
- 1 January 1993
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The design of a new architecture for signal processing, based on the Kolmogorov's theorem (1957), is addressed. This architecture is applied to solve the problem of source separation. Particularly, an adaptive algorithm is proposed to separate simultaneously all the unknown impinging sources on an aperture of sensors. The implemented framework is composed of two different stages: the first one is the inhibition stage, which turns the problem of estimating simultaneous DOAs (directions of arrival) into problems of a single source DOA estimation; and the second one is the optimisation stage which estimates the required parameter in a single signal context easier than the initial one with a multiple signal. A high order rule for learning is described, it improves the behaviour of the system assuring independence of the outputs.Peer ReviewedPostprint (published versionKeywords
This publication has 11 references indexed in Scilit:
- Array covariance error measurement in adaptive source parameter estimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- The Kolmogorov signal processorPublished by Springer Nature ,1993
- EKF Schemes in Array ProcessingPublished by Springer Nature ,1993
- Source separation based on coupled single DOA estimation processorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- Kolmogorov's theorem and multilayer neural networksNeural Networks, 1992
- Multitone tracking with coupled EKFs and high order learningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Blind separation of sources, part II: Problems statementSignal Processing, 1991
- Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architectureSignal Processing, 1991
- Can multilayer mapping networks with finite number of real parameters harness the computational power of Kolmogorov's representation theorem?Published by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Representation Properties of Networks: Kolmogorov's Theorem Is IrrelevantNeural Computation, 1989